Title :
L1/2-constrained morphological component analysis
Author :
Pengliang Yang ; Jinghuai Gao ; Wenchao Chen
Author_Institution :
Xi´an Jiaotong Univ., Xi´an, China
Abstract :
In this paper, we introduce the l1/2 constraint into the morphological component analysis (MCA) to solve the problem of cartoon and texture separation, inpainting and super-resolution for images. The newly proposed iterative half thresholding algorithm is recast in an analysis formulation, and can be well embedded in the MCA framework. Other constraint, such as total variation (TV), can also be combined to enhance the restoration of this modified MCA method. The superiority of the proposed l1/2-constrained MCA method is demonstrated by experimental results.
Keywords :
image resolution; image restoration; iterative methods; L1/2-constrained morphological component analysis; cartoon and texture separation; image inpainting; image superresolution; iterative half thresholding algorithm; modified MCA method; total variation; Compressive sensing; image inpainting; l1/2 regularization; morphological component analysis (MCA); sparse representation; superres-olution;
Conference_Titel :
Signal and Information Processing (ChinaSIP), 2013 IEEE China Summit & International Conference on
Conference_Location :
Beijing
DOI :
10.1109/ChinaSIP.2013.6625298